ISO 42001 Lead Implementer Training Course

ISO/IEC 42001 Artificial Intelligence Management System (AIMS) Lead Implementer Certification Training in Pune

Learn how to design, implement, manage, and improve an AI Management System (AIMS) aligned with ISO/IEC 42001 — the world’s first international standard for AI governance, responsible AI, and trustworthy AI systems.

This training enables professionals to implement AI compliance frameworks, manage AI risks, and ensure ethical AI deployment across organizations.

Why ISO 42001 Certification?

With the rapid adoption of Artificial Intelligence, organizations must manage AI risks, bias, privacy, transparency, and accountability. ISO 42001 helps businesses build responsible AI governance programs and meet regulatory expectations.

Top Job Roles After ISO 42001 Lead Implementer

• AI Governance Manager
• Responsible AI Consultant
• AI Compliance Officer
• AI Risk Manager
• AI Ethics & Policy Specialist
• Data Governance Manager
• AI Security & Trust Officer

Skills You Will Gain

• Implement AI governance framework
• Manage AI lifecycle risks
• Ensure ethical and transparent AI usage
• Align AI systems with regulatory requirements
• Build trustworthy and explainable AI processes
• Integrate AI governance with ISO 27001 & ISO 27701
• Conduct AI risk assessments and impact assessments

ISO 42001 Lead Implementer Course Outline (4 Domains)

Module 1 — AI Governance & Organizational Context

Establish AI governance structure and leadership commitment

Topics Covered:

• Overview of ISO/IEC 42001 standard requirements
• AI principles: fairness, transparency, accountability
• Organizational context & stakeholders
• AI policy development
• Roles & responsibilities in AI governance
• Integration with corporate governance & GRC
• Leadership commitment & culture building
• AI regulatory and legal considerations

Module 2 — AI Risk Management & Impact Assessment

Identify, analyze and treat AI risks

Topics Covered:

• AI risk identification and classification
• Bias detection and mitigation
• AI impact assessment (AIIA)
• Data quality & dataset governance
• Privacy & security risks in AI systems
• Human oversight & accountability
• Model explain ability & transparency
• Continuous AI risk monitoring

Module 3 — AIMS Implementation & Operation

Design and implement Artificial Intelligence Management System

Topics Covered:

• AIMS documentation & controls
• AI lifecycle management
• Model development, validation & deployment controls
• Secure AI system architecture
• Vendor & third-party AI management
• Operational monitoring & logging
• Incident response for AI systems
• Competence & awareness programs

Module 4 — Performance Evaluation & Continuous Improvement

Audit, monitor and improve AI governance framework

Topics Covered:

• Monitoring, measurement & KPIs
• Internal audit of AIMS
• Management review
• Nonconformity & corrective action
• Continuous improvement process
• Documentation & audit evidence preparation
• Certification readiness assessment
• Integration with ISO standards (27001, 27701, 9001)